@compounderfyi · X

我做了一个跟dataroma类似的网站，数据聚合比他完整，大家可以多给我提提意见，多谢！

@ShakibMd93031 · X

Built an Equipment Rental Management System to simplify rentals, payments, and equipment tracking. Looking for businesses interested in a demo or a customized solution.

@codedolphin2 · X

Elias569 · GitHub

fintech-dashboard fintech dashboard for personal finance management which track income and expenses, leverage AI-powered analytics, manage budgets and financial goals, enjoy a dark theme

KORAYTEACHER · GitHub

fintech-advisor ai fintech financial advisor for your portfolio

@HRSuccessCentre · X

Nobody explains the vesting cliff until you've already signed. So here it is in 30 seconds — the wait, the cliff, the drip 🍯 See your own timeline: #Tech #Vesting #Stocks #Recruiting #FreeTool #Builder #VibeCoding

@Portfolio_First · X

My trading platform: Synthetic futures-like spot positions

u/as-333 · Reddit

Built an AI chat that pays you per message, scored in real time: looking for feedback I've been using Claude Code to build Argutum, an AI assistant that scores every message you send (0–100, five dimensions: complexity, novelty, structure, domain expertise, conversational depth) and pays you for the good ones. The underlying idea is that your prompts get sold as training data to AI labs, so you should get a cut instead of it happening for free. Stack: Next.js 16, Groq/Llama 3.3 70B, custom

@PickleCharts · X

Hey @Shakib2O1 Would love to talk to you about my SaaS project ! Drop me a DM

@harryjwang · X

I've used many of the major conference systems. Plenty still have docs as an unsearchable static site — or worse, as PDFs that stopped tracking the product three versions ago. Somehow, still true in 2026. We took an AI-first path with instead. Our docs are generated from the codebase itself. A custom Claude Code skill writes each page and retakes the screenshots whenever a feature changes — so the docs don't drift from the product. Every page still gets reviewed by a human before it ships. Now you can talk to them, too. We just shipped "Ask AI" over our docs: This feature also turned out to be a nice teaching case for agentic RAG vs. classic RAG: • Classic RAG: chunk → embed → vector DB → retrieve once, by fixed rules • Agentic RAG: hand the model a search tool and let it drive — write a query, read the results, rewrite, retry At more than 100 pages, still no vector database needed. And every answer cites the exact page it came from. #Age

@nava_who_codes · X

I spent 46$ to built Fund Explorer app 20$ - Claude Code 12$ - Claude API keys 11$ - Domain 3$ - To test the actual payment gateway after prod deployment

@Caden1Fenn · X

Intel Brief — tracks what your competitors change (pricing, features, positioning) and delivers it to your inbox weekly. Built for indie SaaS founders.